Recently, a low-price RGB-D sensor such as a Kinect sensor of Microsoft Corporation is commercially available, and research is being conducted on a camera tracking method for tracking movement of a camera in real time by using a monoscopic camera, which is classified into Structure From Motion (SFM) and monocular Simultaneous Localization And Mapping (SLAM).
Also, KinectFusion algorithm has been presented, which can reconstruct an image of an indoor environment, which is photographed using a Kinect sensor camera by a moving user, in real time and three dimensions.
The KinectFusion algorithm method may perform a real-time image processing by representing a reconstruction area in a method of storing a Signed Distance Function (SDF) value to a voxel grid, and performing its vast calculation with a Graphic Processing Unit (GPU).
In addition, one of core technologies of the KinectFusion algorithm method is to use not a method of tracking movement of a camera from a relation between two adjacent frames among consecutive input frames (frame-to-frame registration) but a method of combining data between previous frames, generating a model as a result of reconstruction in a middle stage, and tracking movement of a camera from a relation between data of a current frame (frame-to-model registration).
The frame-to-model registration method allows more accurate and stable camera tracking than the frame-to-frame registration method in the related art.
However, the KinectFusion method is suitable for reconstructing a small space or object in three dimensions but not suitable for a complicated and large space, which has the following problems.
A low-price RGB-D sensor camera such as a Kinect sensor is subject to an error. Once the error occurs during a camera tracking process, the error is consistently accumulated, thereby resulting in breaking a reconstruction result.
In order to solve a problem of Loop Closure due to an error generated or accumulated during the reconstruction process, a global optimization method may be used. However, since the method should use data for an entire reconstruction process, it is difficult to be applied to a real-time processing.